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COMPARING BACKUP AND RESTORE EFICIENCY IN MYSQL, MS SQL SERVER AND MONGODB
Abstract
This paper suggests that in order to create efficient backup and recovery strategy for database management system, an appropriate unit of analysis and a proper, data is needed. Key factors for evaluating backup and recovery are time needed to bring the system back online and the amount of data loss. The paper examines methods for managing these factors in three of the most popular DBMS ? MySQL, MS SQL Server and MongoDB. Each of them has a set of backup types that can be combined in different strategies. Depending on characteristics of the database (such as size, modify rate etc.) the combination could lead to efficient results or slowing down the system performance and loss of data. Some advantages and disadvantages of the examined DBMS are found and preferable presets to be used for better efficiency are defined. The reason these findings are important is that they help database administrators to build the best backup and recovery strategy depending on organization's needs
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References15
Banker,K., Bakkum, P., Verch, S., Hawkins, T., Garrett, D., MongoDB in Action, Second Edition, Manning Publications Company, 2016.
Bell, C., Expert MySQL. Apress, 2013.
Fazio, M. et. al., Big Data Storage in the Cloud for Smart Environment Monitoring, Procedia Computer Science, vol. 52, 2015, pp 500–506;
França, W., MongoDB Data Modeling, Packt Publishing Ltd., 2015.
Gartner, [Online] Available from: https://www.gartner.com/doc/reprints?id=1- 2PMFPEN&ct=151013&st=sb [Accessed: 6/05/2017].
Microsoft, Full Database Backups (SQL Server), [Online] Available from: https://msdn.microsoft.com/en-us/library/ms186289.aspx [Accessed: 14/05/2019].
MongoDB, MongoDB Manual, [Online] Available from: https://docs.mongodb.com/manual/ [Accessed: 14/05/2019].
MySQL, MySQL 5.7 Reference Manual, [Online] Available from: https://dev.mysql.com/doc/refman/5.7/en/ [Accessed: 15/05/2019].
Panayotova, G., Dimitrov, G., Petrov, P., Bychkov, O. Modeling and data processing of information systems. 3rd International Conference on Artificial Intelligence and Pattern Recognition (AIPR), Lodz, Poland, IEEE, 2016, pp 154- 158;
Polkowski, Z., Vasilev, J., Zajac, D., Florina, A.L. A content analysis of existing educational portals for teaching data warehouse and business intelligence, Proceedings of the 8th International Conference on Electronics, Computers and Artificial Intelligence, Romania, ECAI 2016, 7861146, 2016.
Schwartz, B., Zaitsev, P., Tkachenko, V., High Performance MySQL: Optimization, Backups, and Replication, O'Reilly Media Inc, 2012.
Shichkin, A., Buevich, A., Sergeev, A., Baglaeva, E., Subbotina I., Vasilev J., Kehayova-Stoycheva, M. Training algorithms for artificial neural network in predicting of the content of chemical elements in the upper soil layer, AIP Conference Proceedings pp. 060004-1 - 060004-5, DOI: 10.1063/1.5082119, 2018.
Sulova, S., Integration of structured and unstructured data in the analysis of e-commerce customers, International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, Albena, vol.18, pp. 499-506, 2018.
Sulova, S., Todoranova, L., Penchev, B., Nacheva, R., Using text mining to classify research papers, 17th International Multidisciplinary Scientific Geoconference SGEM, Albena, vol.17/ issue 21, pp 647-654, 2017.
Vaswani, V., MySQL Database Usage & Administration, McGraw Hill Professional, 2009.
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Number of times cited according to Crossref: 10
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